Climatic Change, Wars and Dynastic Cycles in China Over the Last Millennium

CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES IN CHINA OVER THE LAST MILLENNIUM

DAVID D. ZHANG1,C.Y.JIM1, GEORGE C-S LIN1, YUAN-QING HE2, JAMES J. WANG1 and HARRY F. LEE1 1Department of Geography, University of Hong Kong, Pokfulam Road, Hong Kong E-mail: [email protected] 2CAREERI, Chinese Academy of Science, Lanzhou 730000, Gansu, China

Abstract. In recent years, the phenomenon of global warming and its implications for the future of the human race have been intensively studied. In contrast, few quantitative studies have been attempted on the notable effects of past climatic changes upon human societies. This study explored the relationship between climatic change and war in China by comparing high-resolution paleo- climatic reconstructions with known war incidences in China in the last millennium. War frequencies showed a cyclic pattern that closely followed the global paleo-temperature changes. Strong and significant correlations were found between climatic change, war occurrence, harvest level, population size and dynastic transition. During cold phases, China suffered more often from frequent wars, population decline and dynastic changes. The quantitative analyses suggested that the reduction of thermal energy input during a cold phase would lower the land carrying capacity in the traditional agrarian society, and the population size, with significant accretions accrued in the previous warm phase, could not be sustained by the shrinking resource base. The stressed human-nature relationship generated a ‘push force’, leading to more frequent wars between states, regions and tribes, which could lead to the collapse of dynasties and collapses of human population size. War frequencies varied according to geographical locations (North, Central and South China) due to spatial variations in the physical environment and hence differential response to climatic change. Moreover, war occurrences demonstrated an obvious time lag after an episode of temperature fall, and the three geographical regions experienced different length of time lags. This research also shows that human population increases and collapses were correlated with the climatic phases and the social instabilities that were induced by climate changes during the last millennium. The findings proposed a new interpretation of human-nature relationship in the past, with implications for the impacts of anomalous global warming on future human conflicts.

1. Introduction

The relationship between civilization and climatic change is of fundamental impor- tance, so much so that it can facilitate the rise or demise of culture (Cowie, 1998). It has been a long-standing belief that climatic change would lead to social, cultural and economic repercussions in human societies. For instance, Hsu (1998) advocated that micro-changes of temperature exerted notable inﬂuences on the fate of human civilization. Recently, important attempts have been made to use high-resolution paleo-climatic record to explain several pre-historical cultural breaks in certain time periods (deMenocal, 2001; Polyad and Asmerom, 2001; Weiss and Bradley, 2001; Wu and Liu, 2002). Extensive documentation has been made in attempts to

Climatic Change (2006) 76: 459Ð477 DOI: 10.1007/s10584-005-9024-z c Springer 2006 460 DAVID D. ZHANG ET AL. assess the causes of wars (e.g., Pruitt and Snyder, 1969; Westing, 1988; Seabury and Codevilla, 1989; van Evera, 1999; Ge et al., 2002), but none tackled specifically the climatic change-war relationship. Webster’s (1975) study of pre-historical and early-historical societies suggested that warfare is an adaptive ecological choice under the conditions of population growth and resource limitation, although he did not obtain systematic scientific data to support his thesis. Malthus (1798) and many ecological studies considered that when a species (including human) population size exceeded a certain threshold that could not be supported by available resources, the population would crash. Such a collapse in human population, in Malthus’ view, was partially achieved by wars. The association between wars and the environment has been recognized by some researchers (Ferguson, 1984; Stranks, 1997; Suhrke, 1997; Cowie, 1998). However, the existing literature tends to focus on the social and economic costs of current and future environmental changes. We believe that learning how past climatic changes had influenced human society is crucial to understanding the current human-nature situation and predicating the future. The last three decades witnessed intensive research on past climatic change around the world. The last 10 years work, in particular, has ushered significant improvements in high-resolution paleo-climatic reconstructions, using multi-proxy data networks to reconstruct past climate variations. A focus on the last millennium showed the global warming trend, from which it has been concluded that the last century was the warmest (Jones et al., 2001; Mann et al., 2003). It is reckoned that such refined paleo-climatic records could provide a strong basis to evaluate the intricate relationship between climatic change, wars and dynastic transitions. The large land area and geographical variations in China have permitted climate to express itself explicitly in its varied natural and cultural landscapes, and associated modes of human occupancy and livelihood. The effect of climate has had the most far-reaching and persistent historical imprints on the country (Chang, 1946). In investigating the relationships of climate-war and climate-dynastic cycle, China would afford an excellent case study. In the course of China’s long history, volu- minous documentation in the palace archives of different dynasties, dating back to 880 BC, systematically recorded all major events. This valuable and comprehensive information repository provided a rich database for our study. We propose the hypothesis that long-term climatic change has brought significant shifts in land carrying capacity which could be considered as a variable in history. This view is contrary to the traditional one of Malthus, Darwin and many ecologists who hold land carrying capacity as a constant. Such capacity shifts could have influenced the well-being of the humankind socially, econom- ically and culturally not only in pre-historical time but also in recent history of agricultural societies. In favorable climatic phases, the land carrying capacity increased, the conflict for resources was reduced and the population grew fast. When climate became unfavorable, resulting in capacity decline, the population size with much accretions accumulated in the previous favorable period could not be sustained. Therefore, armed conflicts for limited resources largely increased in more CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 461 populated areas that could consequently lead to population crash and dynastic collapse. These perceived climate-war and climate-dynasty relationships have never been substantiated with scientific evidence. In this study, we adopted a new ap- proach to analyze quantitatively the climate-war and war-society relationships at the macro-scale, by comparing the paleo-climatic series with war, population and historical sequences. Through this high-resolution comparison, the degree of influence extended by climatic change on wars and historical events may be examined and our hypothesis tested.

2. Data and Methods

A group of researchers from the Nanjing Academy of Military Sciences has compiled a multi-volume compendium that records exhaustively information on the wars that took place in China from 800 BC to AD 1911 (Editorial Committee of China’s Military History, 1985). The book includes an appendix with details of each war, including its inception year, participants, location, causes, and in most cases, the number of soldiers or combatants, casualties, proceedings and results. All of the 1672 wars listed in the authoritative treatise from AD 1000 to 1911 have been used as the database for this study. To avoid bias associated with different sources of information, only the reliable variables were used for scientific analysis, including year of inception, number, participants and location of the wars. Based on such information, the frequency, participant-type and geographical distribution of the wars can be calculated with reference to a time series. Some wars without reliable information on locations were put in an unidentified category. War classi- fication was based on the types of participants, particularly leaders of the two sides in the armed conflicts. The wars were grouped into rebellion and others (state and tribal wars). The times of dynastic changes were based on official records published by government bodies and historians. The dynasties included those that ruled most parts of China, and those established by remote tribes that once occupied an area equivalent to over 10 provinces of the current Chinese territory. The geographical occurrence of wars helped the assessment of climate-war association. According to the basic principles of physical regionalization of China (Ren et al., 1985; Zhao, 1986), China is divided into three macro regions for this study, namely: (1) North China with continental humid, semi-humid, semi-arid and arid temperate climate influenced by both the monsoons and the westerlies. Its average annual temperature ranges from very low to 14 ◦C. Major agriculture products are spring wheat (northern part) and winter wheat (southern part). Economic activities are mainly pastoral because the relatively low average annual precipitation of 50Ð750 mm, with over 100 frost days per year. (2) Central China with a climate dominated by the monsoons, with annual temperature ranging from 14 to 18 ◦C, and 10Ð80 frost days per annum. The region has served as China’s major rice 462 DAVID D. ZHANG ET AL.

Figure 1. Physical regionalization and major agricultural products of China. producing area. (3) South China with a south subtropical and tropical climates and average annual temperature ranging from 19 to 22 ◦C. The long growing season permits double- or triple-cropping in a year. Frost days are less than 10 per annum (Figure 1). Briffa and Osborn (2002) chose the five most representative and the latest climate series of the last millennium in the Northern Hemisphere, including the data from China, to discuss the differences between the records of various independent studies (Figure 2a). Despite the diverse sources of data, all five high-resolution climate records register close matching of warm and cold phases. Such congruence of data acquired independently by different authorities suggested a high degree of accuracy with reference to both temperature and timing. These climatic series provided a reliable basis to investigate the relationships between climatic changes and historical events in China. The records from AD 1000 to 1980 have been adopted as the standard climate variations in this study. These records were reconstructed by using multi-proxy data, including tree ring, coral, ice-core, borehole and historical document studies. The data were recalibrated by Briffa and Osborn (2002) with linear regression against the AD 1881Ð1960 mean annual temperature observations averaged over the land area north of 20 ◦N, and the results were smoothed with a 50-year filter. The recalibrated records were then averaged by us in order to quantitatively define the boundaries of the cold and warm phases. A cold or warm phase would be determined if the average temperature change (bold black line, Figure 2a) has an amplitude exceeding 0.14 ◦C, in order to get an equal aggregate duration of cold and warm periods. Six major cycles of ‘warm’ and ‘cold’ phases have been identified from AD 1000Ð1911 based on the average reconstruction. These phases were also reflected in many other climatic reconstructions of China CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 463

Figure 2. Climatic changes and incidence of wars in China during the last millennium. (a) Normalized temperature change records for the last millennium for land areas in the Northern Hemisphere north of 20 ◦N: Cowley and Lowery (1997, turquoise line); Jones (1998, dark blue line); Mann (1999, pink line); Briffa (2000, yellow line); Esper (2002, violet line) and the average of these five normalized series (bold black line). Cold phases are shaded as gray strips. (b) Frequency of total wars (sky blue line) and frequency of rebellions (red line). (c) Frequency of wars, in North China (red line); in Central China (sky blue line); and in South China (bright green line). (d) Dynastic changes and population size (in million) in China. 464 DAVID D. ZHANG ET AL. and North Hemisphere (e.g., Zhang et al., 1981; Seabury and Codevilla, 1989; Wang, 1990; Ge et al., 2002; Mann et al., 2003). The boundaries between warm and cold phases were delineated at the mean temperature point between minimum and maximum values of two contiguous phases on the average reconstruction. The aggregate duration of the cold phases was 459 years and of the warm phases 453 years. The cold phases spanned AD 1110Ð1152, 1194Ð1302, 1334Ð1359, 1448Ð 1487, 1583Ð1717 and 1806Ð1911, and warm phases AD 1000Ð1109, 1153Ð1193, 1303Ð1333, 1360Ð1447, 1488Ð1582 and 1718Ð1805 (Figure 2a). Although a few paleo-temperature reconstructions have been conducted in China and their changes basically followed the above constructions, the resolution of such reconstructions did not reach the annual scale that we achieved in this research. Therefore, we decided to use the five constructions quoted by Briffa and Osborn (2002) as the standard paleo-temperature records of the last millennium. The link between war, climatic change and quantitative harvest information during the last millennium is very important in testing our hypothesis. Whereas wars and climatic change are comparatively well documented, it proved very difficult to obtain records of agricultural production over a long period because most dynasties in the study period had no proper registry system to collect such data. Fortunately, records were compiled under the ‘Baojia’ system introduced in China during the Qing Dynasty (AD 1644Ð1911), which stored population, harvest and land data for taxation and other administrative purposes. This valuable archive allowed a comparison of harvests in China at 66 different localities in AD 1730Ð1900 (Gong et al., 1996), which covered a cycle of warm and cold phases for verification of temperature-change impacts on harvests. It has been quantitatively proved that shifts in land carrying capacity that followed climatic changes brought cyclic growth and collapse of the Mesopotamian population (Johson and Gould, 1984), and that long-term climatic changes had brought fluctuations of population size in mid-latitude countries in the 17th century (Galloway, 1986). However, no study has been attempted on the long-term time series of population change in conjunction with the corresponding highly accurate temperature data. According to our hypothesis and Webster’s (1975) view, population pressure resulting in reduced food supply per capita is another important cause of wars. The population data were retrieved from Jiang (1993) who reviewed many population records and studies and provided reliable population fluctuations from 206 BC. We adapted the record from AD 1000 onwards (Figure 2d).

3. Results

3.1. FREQUENCY OF WARS AND CLIMATIC PHASES

Like climate variations, the war frequency in China demonstrated a cyclic pattern, with a turbulent period followed by a relatively tranquil one (Figure 2b). CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 465

War frequencies were summed by decades and grouped into four classes: very high (>50 wars/10a), high (25Ð50 wars/10a), moderate (10Ð25 wars/10a) and low (<10 wars/10a). Eight out of the ten peaks above the very high and high groups coincided with cold phases. Three high peaks stood well above others (Figure 2b, sky blue line), two of which occurred in the coldest phases (c. <−0.5 ◦C). All cold phases have one or two high war frequencies. Wars generally occurred with a time lag of 0Ð30 years after the initiation of a cold phase. Only two high peaks fell out- side the cold phases (the aberrant peaks) and they both occurred in the 16th century. Although some temperature declines could be observed in this period, they were not enough to be classiﬁed as a ‘cold phase’. Rebellion was the dominant war category (Figure 2b, red line). The variation of the rebellion frequency is highly correlated with climatic changes. The aberrant peaks, overshadowed by this correlation, were mainly brought by nomadic invaders from the north and wars with pirates intruding from overseas. The geographical distribution of these historical wars (Figure 2c) depicted an interesting pattern. In warm and humid South China, war frequency variations were less sensitive to temperature changes. War outbreaks in North China were closely associated with cold phases, and war frequencies remained at a relatively constant higher level in AD 1300Ð1600. Six of the seven highest war peaks in Central China occurred in cold phases, and they all closely followed cold phases. When cold phases started, wars in North China immediately broke out, except the cold phases in the 14th and 19th centuries when China was ruled by northern nomadic tribes (respectively, Mongol and Manchu). In contrast, high war frequencies in Central China generally had a 10Ð30 year time lag behind the highs of North China, and a 20Ð50 year time lag after the cold phases started. The wars ushered notable societal changes that could eventually induce the collapse and establishment of dynasties in AD 1000Ð1911 (Figure 2d). All dynastic changes during the study period basically occurred in cold phases with high war frequencies, except the Yuan Dynasty collapse and the establishment of Ming and Xixia Dynasties (Figure 2d and Table I). Of the six cold phases in the last millennium, ﬁve had experienced dynasty collapse.

3.2. STATISTICAL ANALYSIS

To reﬁne the analysis, the number of wars in each phase was calculated and the ratios of wars in warm and cold phases were compared (Table II). The results show a pattern consistent with the above observation. Although wars could be induced by other underlying causes and their response to temperature change had a time lag (cf. Section 3.1), the correlation analysis between temperature anomaly and war frequency still revealed notable associations between climatic change and war occurrence. Pearson’s correlation coefﬁcients between war frequency and temperature anomalies have been computed at three different time scales: phase, decade and annual. 466 DAVID D. ZHANG ET AL.

TABLE I Relationships between climatic phases, wars and dynastic changes

Average temperature Climatic Number War Dates of dynastic ◦ Year (AD) anomaly ( C) phases of wars ratios changes (AD)

1000Ð1109 −0.252 Warm 135 1.23 1110Ð1152 −0.368 Cold 93 2.16 Establishment of Jin (1115), collapses of North Song (1127) and Liao (1125) dynasties 1153Ð1193 −0.315 Warm 41 1.00 1194Ð1302 −0.419 Cold 252 2.31 Establishment of Great Mongol (1206) and Yuan (1271), collapses of Jin (1234), South Song (1279) 1303Ð1333 −0.362 Warm 33 1.07 1334Ð1359 −0.454 Cold 90 3.46 1360Ð1447 −0.345 Warm 189 2.15 Establishment of Ming and collapse of Yuan (1368) 1448Ð1487 −0.461 Cold 89 2.23 1488Ð1582 −0.392 Warm 208 2.19 1583Ð1717 −0.534 Cold 266 1.97 Establishment of Qing (1636) and collapse of Ming (1645) 1718Ð1805 −0.413 Warm 72 0.82 1806Ð1912 −0.456 Cold 204 1.93 Establishment of the Republic of China and collapse of Qing (1911)

TABLE II Number of wars and ratio of wars in cold and warm phases in different war categories

Total wars Rebellions Others North Central South

Cold phases (459 years) 994 536 69 351 462 116 Warm phases (453 years) 678 275 53 278 237 110 Ratio of wars (cold/warm phases) 1.47 1.95 1.30 1.25 1.95 1.06

The phase scale calculation could determine whether war outbreak was re- lated to low or average temperature anomalies. In each phase, the highest war frequency, the lowest temperature and average temperature anomalies were included in the calculation. The results showed that the highest frequencies of total war, rebellion war and Central China war were signiﬁcantly correlated with both the lowest and average temperature anomalies of the phases (Table III). The correlations at the decade scale were computed between the number of wars in each decade and the lowest and average temperature anomalies with 0Ð30 year CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 467

TABLE III Pearson’s correlation coefﬁcients

Total wars Rebellions Others North Central South

Between average temperature anomalies and the highest war frequencies in each climatic phase −0.693∗ −0.686∗ −0.014 −0.511 −0.666∗ −0.525 Between the lowest temperature anomalies and the highest war frequencies in each climatic phase −0.707∗ −0.707∗ −0.084 −0.516 −0.697∗ −0.576

∗ Signiﬁcant at 0.05 level (two tailed).

TABLE IV Pearson’s correlation coefﬁcients

Time lag (year) Total wars Rebellions Others North Central South

Between average temperature anomalies and number of wars in each decade 0 −0.179 −0.229∗ 0.030 −0.090 −0.214∗ −0.065 10 −0.223∗ −0.268∗ −0.010 −0.133 −0.274∗ −0.043 20 −0.200 −0.252∗ 0.026 −0.076 −0.271∗ −0.065 30 0.122 −0.204 0.096 0.024 −0.225∗ −0.106 Between the lowest temperature anomalies and number of wars in each decade 0 −0.177 −0.240∗ 0.052 −0.090 −0.220∗ −0.071 10 −0.213∗ −0.268∗ 0.029 −0.137 −0.260∗ −0.042 20 −0.200 −0.258∗ 0.036 −0.083 −0.275∗ −0.051 30 −0.114 −0.203 0.109 0.300 −0.223∗ −0.090

∗Significant at 0.05 level (two tailed). time lags. The numbers of rebellions and wars in Central China were significantly correlated with the lowest and average temperature anomalies for most time lag durations (Table IV). The number of total wars is significantly correlated only with both anomalies at the 10-year time lag. Such differences also appeared in the annual scale correlation analysis. Each year’s war counts were significantly correlated with temperature anomalies in the categories of total war, rebellion and Central China war for 0Ð30 year time lag (Table V). It is very interesting that North China wars, not correlated with temperature anomalies at phase and decade scales, were significantly correlated with annual temperature anomalies at 5-, 10- and 15-year time lags. The highest correlation coefficients for different time lags varied with war categories. For rebellion, total war and Central China war, most correlated time lags were 10Ð15 years, comparing with North China war at 5Ð10 years. 468 DAVID D. ZHANG ET AL.

TABLE V Pearson’s correlation coefﬁcients between annual temperature anomalies and annual war records

Time lag (year) Total wars Rebellions Others North Central South

0 −0.115∗∗ −0.156∗∗ 0.026 −0.060 −0.133∗∗ −0.034 5 −0.143∗∗ −0.178∗∗ 0.009 −0.086∗∗ −0.160∗∗ −0.024 10 −0.153∗∗ −0.191∗∗ 0.008 −0.086∗∗ −0.179∗∗ −0.021 15 −0.152∗∗ −0.192∗∗ 0.012 −0.073∗∗ −0.183∗∗ −0.023 20 −0.142∗∗ −0.180∗∗ 0.013 −0.052 −0.178∗∗ −0.033 25 −0.117∗∗ −0.162∗∗ 0.030 −0.021 −0.163∗∗ −0.042 30 −0.091∗∗ −0.145∗∗ 0.050 0.012 −0.151∗∗ −0.046

∗∗Signiﬁcant at 0.01 level (two tailed).

4. Analysis and Discussion

4.1. WAR FREQUENCY AND TEMPERATURE CHANGES

In the last millennium, the high degree of match between war frequencies and cold phases, and the signiﬁcant correlations between temperature anomalies and war numbers, could not have happened simply by accident or chance. It is believed that the reduction of thermal energy input in cold periods was the root cause of social unrest and uprising. In the ‘Little Ice Age’, many places around the world experienced famine (Ponte, 1976; Bryson and Murray, 1977) and witnessed large-scale population migration (Hsu, 1998) literally in search of food. As an overwhelmingly agrarian society, China’s main source of livelihood was agriculture. Traditional agriculture was very much dictated by the whims of climate and weather conditions. Any reduction of thermal energy input would trim agriculture production. Accord- ing to Gong et al. (1996), agricultural yields in China in AD 1840Ð1890 (cold phase) was reduced by 10Ð25% in comparison with AD 1730Ð1770 (warm phase), because the cold periods shortened the growing season and increased frost days and cold spells. Signiﬁcant yield reduction caused by cooling was also evidenced by the history of rice cultivation in the middle and lower reaches of the Yangtze River. Double cropping of rice started in Tang Dynasty (AD 618Ð906), as an innovation in agricultural technology, and was further developed in the late 15th century in Ming Dynasty (AD 1368Ð1643). The double cropping, however, failed in AD 1620Ð1720 because of the colder weather, and thereafter in AD 1720Ð1800 it recovered and dominated the region again. In the 19th century, double cropping in the region failed again despite the government’s promotion of the techniques (Yin et al., 2003). In the region, all previous periods of double cropping successes coincided with warm phases, and at present the system is functioning well. Our quantitative study sought to use records across a long time frame to determine whether variations in agricultural CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 469

Figure 3. Temperature anomalies and harvest variations in China during AD 1730Ð1910. Temperature anomalies (bold black line) correspond to the right Y-axis; while autumn and summer harvest records (cross- and circle-dotted lines) correspond to the left Y-axis. Harvest records are expressed in terms of indexes to exceptionally good historical harvests (max. = 10) and smoothed by the Butterworth low- pass ﬁlter. Correlation coefﬁcient between temperature anomalies and the autumn (summer) harvest indexes in China during AD 1730Ð1850 is 0.854 (0.764), P < 0.01.

production were correlated with temperature changes. The AD 1730Ð1850 records demonstrated that the average summer and autumn harvests in China also followed congruently the temperature changes (Figure 3). Yield reduction would trigger famine, tax revolt and a weakening of state power. The deficit in livelihood resources was aggravated by the population expansion accumulated in the previous warm period. Thus rebellions and state wars were likely to erupt during the cold phases. It is notable that rebellions were predominantly mobilized by peasants in the cold phases. The three highest peaks of war frequency actually represented three of the most notable peasant rebellion periods in Chinese history, namely Taiping, Mingmo, Yuanmo rebellions. Comparing Figure 3 with Figure 2, we found that the outbreak of Taiping rebellion occurred when harvests fell to a critical level. A significant consequence of this rebellion was the reduction of China’s total population from 440 million in AD 1850 (the year of Taiping rebellion outbreak) to 360 million in AD 1865. Such a population crash would shrink greatly the agrarian workforce and left a serious carry-over effect on harvest level. Even though the climate became warmer after the rebellion, agricultural production remained low for some time (Figure 3). The time lags of high war frequencies in cold phases and of war occurrences in decadal and annual scales have important implications on the bearing capacity of society, which could be explained in two ways. The first is that the reduction of livelihood resource would not immediately generate social unrest because the storage of agricultural products could sustain people for some time, so was the state power. The second explanation is due to the development of a better social 470 DAVID D. ZHANG ET AL. organization which could provide a cushion to prolong the lag-time from the first to the last cold phases in the millennium. The correlation analysis provided a quantitative expression of the war- temperature relationship. It is not surprising that the highest war frequency, average temperature and lowest temperature anomalies were significantly correlated in the categories of the total war, rebellion and Central China war at the phase scale. This is due to the fact that prolonged cooling had exhausted the stored livelihood resources and eventually brought wars. We did not expect that the temperature anomaly shifts at the decadal and annual scales were significantly associated with wars. This is because the temperature anomaly series is averaged and smoothed values and many short-term climate extremes could not be shown in the curve. However, even without the influence of temperature extremes, the correlation analyses at the short-term scale still verified that war number is significantly correlated with the trend of Northern Hemisphere temperature changes.

4.2. GEOGRAPHICAL PATTERN OF WARS

The geographical distribution of wars lent further supports to our hypothesis (Figure 2c). In humid tropical and subtropical South China, the influence of cooling in cold phases on agricultural production might have a subdued effect on resource reduction because of rich endowment in heat and moisture in the coastal region. Even if cooling were severe enough to affect cropping, the more flexible farming system in the South, with a wide range of domesticated species, could adopt alternative crops. Therefore, human reaction to cooling in South China had not been so sensitive and severe. In contrast, the climate in Central China is controlled by the monsoons: cold-dry air masses move in from Siberia in the winter and warm-humid marine air masses come in from the southeast and southwest in the summer. Although the cold phases reduced agricultural yield, the outbreak of wars generally demonstrated a delay after the cold period started because, unlike North China, surplus farm products could be stored to serve as a buffer in difficult times. Besides, the better heat and water resources there allowed the hardship and associated dissatisfaction of the society to take some incubation time to reach its breaking point. In other words, the high war frequencies clearly echoed more stringent resource conditions. This observation also explained why the cold phase in mid-15th century did not cause a very high war frequency. This cold phase was very brief (39 years), preceded by a rather long warm phase (84 years) with good harvest. It should be noted that many studies of China’s paleo-climate indicated that the cold periods were dominated by winter monsoons from Siberia and hence were drier than warm periods (An, 2000; Li et al., 2000). Thus cold periods could have imposed a double jeopardy in terms of coldness and dryness, bringing a highly stressed condition for agriculture. However, precipitation changes in China were more complicated in terms of its regionality and amplitude than temperature changes and further studies are needed. CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 471

TABLE VI Pearson’s correlation coefﬁcients between annual temperature anomalies and annual war records of North China during the period without northern tribe occupation

Time lag (year) 0 5 10 15 20 25 30

Pearson’s correlation −0.208∗∗ −0.238∗∗ −0.233∗∗ −0.222∗∗ −0.217∗∗ −0.201∗∗ −0.183∗∗ coefﬁcients

∗∗Signiﬁcant at 0.01 level (two tailed).

North China, where the main sustenance was grazing, was sensitive to cooling which could reduce short-term production and trigger long-term loss of ecosystem productivity due to land degradation and desertification. In addition, unlike crop produce, the pastoral animal resources could not be stored for a long time. Thus in the north the onset of a cold period would soon be followed by wars. This phenomenon was reflected in the changes of correlation coefficients of different time lags, showing that the significant war reactions to cooling were five years earlier than Central China. Many wars involved the invasion of desperate nomadic people from the grasslands in Mongolia to the fertile land in Central China. It could be noted, however, that the cold-warm ratio of wars in North China is not higher than that of Central China, and the correlation between temperature anomaly and war number is only significant in 5Ð15 year time lags at the annual scale, although most of the high frequencies occurred in cold phases. At the time when the whole China or part of Central China was ruled by northern nomadic tribes (South Song, Yuan and Qing Dynasties), which covered more than 500 years and over half of the study period, people in the north could freely shift to the south or acquired their livelihood from the south, thus the war frequency in North China was reduced in the cold phases (respectively in the 13, 14, 17 and 19th centuries). This point could be corroborated by the fact that wars in North China had lost their leading role in the countrywide uprisings occurring in cold phases in the 14 and 19th centuries (Figure 2c). At the annual scale correlation analysis, if we disregard the occupation years, the correlation between temperature anomaly and war number in North China was more significantly correlated with the temperature anomaly than other areas (Table VI).

4.3. POPULATION AND TEMPERATURE CHANGES

Five demographic collapses occurred during the last millennium, each with population losses ranging from over 30 million to 80 million (Figure 2d). These collapses happened in cold phases and coincided with high war frequencies and dynastic changes. On the contrary, all warm phases had fast population growth. Ecologists and population biologists have long used the logistic model of population dynamics 472 DAVID D. ZHANG ET AL. to understand the cause-effect relationship between carrying capacity and population size (Hopfenberg, 2003). The model, embodying the ideas of Malthus and Darwin, considered that the population growth before industrialization presented a sigmoidal or S-shaped curve and the land carrying capacity for supporting humans was a constant. Therefore, human population collapses in history were generally explained by the population exceeding the limit imposed by carrying capacity. Our analysis, however, showed that such population collapses were initiated by the reduction of land carrying capacity, not by population growth per sec. In cold phases, the threshold of land carrying capacity was reduced and the population accrued in the previous warm phase was trimmed by cultural responses to natural changes, namely the attrition of war, famine and dynastic change. In warm phases, the threshold of land carrying capacity was raised and the population growth quickly rebounded to catch up with the elevated limit. Such fast population growth un- doubtedly created the underlying condition for the next population crash in a cold phase. Such crashes were explained by the impacts of famine, war and epidemics (Malthus, 1798). However, it seemed that war was the major and root cause of periodic population crashes in China. In the last millennium, the lag times (within a range of 5Ð50 years) for population collapses were gradually extended from the first to last cold phases. This could be explained by gradual introduction of new crops, improvement in food production and storage and irrigation technologies. Such developments, coupled with a mild climate, trade, urbanization and possibly the improvement of social organization, led to a population surge in the 18th century. This may imply that technological advancements since the 18th century have increased the land carrying capacity to a certain degree and reduced the climate-dependence of human population. The climatic reconstructions also showed a gradual cooling trend since AD 1000 and before the 20th century. Such climatic impact on bio-productivity forced people in the north to migrate towards the south. Chang (1946) indicated that southward movement of the population from the less to the more favorable climatic regions was the major internal migration trend of China in historical times. Since the inception of the Song Dynasty (AD 960), China’s economic and cultural centers had shifted southward particularly to the fertile land of the Yangtze River Delta (Central China), as the northern wheat and pastoral regions could not support a population as dense as the rice region. Since then over 60% of the Chinese population lived in the Central and South. This shift reflected human response to the gradual global cooling trend from the 1000s to 1900s, which was followed by global warming since 1900s. Fang (1992) identified two waves of southward migration in China in the last millennium, namely in AD 1000Ð1300 and AD 1630Ð1900. All three long cold phases in the last millennium fell into these two periods. From early 1900s until recently, a reverse movement towards the north, mainly from the over-populated Shandong and Henan Provinces to the relatively sparsely populated Northeast China, reduced slightly the population share of south China in 1984 to 57% of the national total. CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 473

4.4. DYNASTIC CYCLES AND CLIMATIC CYCLES

The philosopher Mencius (374Ð288 BC) perceptively observed that a period of order was perforce followed by a period of disorder. The Chinese believed generally that a minor disturbance was expected every thirty years and a major one every one hundred years (Hsu, 1995). Interestingly, during the last millennium the cold phases of the average reconstruction could be divided into long ones each lasting 105Ð133 years and short ones about 25Ð43 years. The major disorders often coincided with the collapse of dynasties. Western scholars have described this phenomenon as ‘dynastic cycle’, the study of which has engendered a host of economic, evolution and development explanations of Chinese history (Hartwell, 1967; Elvin, 1973; RWGCRST, 1979). As observed in Figure 2d, the start and end of a cycle were basically associated with cold periods during the last millennium. The established cyclic theories attempted to explain the up-down pattern as the consequence of social evolution or internal mismanagement. However, none of the existing theories has ever presented systematic evidence to sustain the hypothetical elaboration. Moreover they neglected the influence of environment or climate as a direct causal mechanism. Skinner (1985) provided a diagram to show regional cycles of development of North China and Southeast Coast based on documentary records. Our study found that the three episodes of economic decline of North China in the last millennium were associated the three longest cold phases which also experienced the highest war occurrences. In contrast, the economy of Southeast Coast was basically expanding during these three periods. The shift of economic centers in China was explained by opening of trade, change of politic center and foreign invasion. The development cycles were incorporated into the dynastic cycles, the movement of which depended on the military power, administrative efficiency and fiscal strength and stability (Skinner, 1985). Skinner also mentioned about putative links between climatic cycles and cycles of economic prosperity and indicated that, if such speculations were borne out in future research, the long-term cycles of climate could help to explain the long-term cycles of Chinese economic activity. Our findings suggested that climatic change was closely associated with war frequency because the shortage of livelihood resources in cold periods could trigger wars. The outbreak of wars would further weaken state power, eventually leading to dynastic collapse. It can be noted that the three long cold phases in the last millennium had brought about the collapse of the three longest dynasties: Song, Ming and Qing. Therefore, the climatic cycles should be incorporated in the cyclic theories in future studies.

5. Conclusion

Climatic change has played a very important role in Chinese history in the last millennium. When global cooling occurred, the war number increased significantly 474 DAVID D. ZHANG ET AL. because of shrinking livelihood resources exacerbated by the large population ac- cretion in the previous warm phase. High war frequency caused the collapse of dynasties and population. The impacts of cooling varied in the three major geographical regions of China. In North China, cooling would generate social unrest very quickly because of its dominant pastoral practice. War frequency in South Chin had little correlation with cooling due to its humid subtropical and tropical climate where small temperature decline could hardly affect yields from the predominant arable agriculture. The outbreak of wars in Central China responded closely to cooling, but with a very obvious time lag of generally 10Ð20 years. Such delays reflected the cushion effect of crop food storage for a certain period of time. The findings of this study could raise issues of theoretical and empirical sig- nificance. Traditional wisdom would explain the fundamental causes of wars as economic, political, ethnic, and recently also environmental. None of these rea- sons deals specifically the contribution of climatic change. Our research indicated that climatic change indeed played a very important role in the switch of dynasties and the associated societal evolution, and was the major underlying cause of wars and cyclic population variations in long-term scale. Analyzing the relationship between population size and temperature variations also showed that human population growth followed closely the shifting limit of land carrying capacity, including periods when the capacity was augmented rapidly by technological advancement. With the lack of a safety margin in good times, the onset of bad times associated with cooling would bring fast responses expressed as population shrinkage. There- fore, the risk of population collapse due to climatic change still exists in the modern era. Currently, the issue of global warming has attracted much research inquiries and attention. It must be pointed out that, unlike the ‘warm phase’ we discussed above, the global warming is an unprecedented warming event in the last two millennia (Mann, 2003; Moberg et al., 2005). As a rather novel climate extreme opposite to cooling, the increase in global temperature could similarly incur hazards to small- scale farming that still supports most people around the world. In addition, the humankind and the Earth’s ecosystems have never experienced such a magnitude of warming in the last two millennia, and it is possible that the global temperature will continue to rise in the near future. We are still uncertain as to the extent human impacts could influence natural changes. Further research is needed to assess the possible armed conflicts as a response to the underlying global warming trend, and especially that the human population has reached such a dangerously high level in a world with stressed resource supply. Even if food supply problem would not arise in highly developed societies, the shortage of other essential resources due to climatic change, such as fresh water, land area, energy and minerals, plus the endless demand for a higher standard of living, would very likely trigger armed conflicts among human societies. CLIMATIC CHANGE, WARS AND DYNASTIC CYCLES 475

Acknowledgments

We would like to thank the supports from the RGC grant (HKU7243/04H) of the HKSAR Government and the Outstanding Researcher Award from the University of Hong Kong, Dr. K.R. Briffa for providing paleo-climatic reconstructions, and Miss Angel K.Y. Ng for the identiﬁcation of war locations.

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(Received 6 August 2005; accepted 18 August 2005)